Creating a dictionary in pandas by mapping column values to headers

Question

I have the following data frame:

F1:


head       drowsiness     sweat       
head_P     D_P            sw_f
head_S     D-H            sw_h
head_F     D_L            sw_l

I need to create a dictionary by mapping all the values in columns to the header of the columns as follows:

Dic = {head_p:head, head_S: head, head_F: head,  D_P: drowsiness, D-H:drowsiness ,  D_L: drowsiness,   sw_f: sweat,  sw_h: sweat , sw_l: sweat }

I created a list of each column and mapped it to the header, but I do not know how to create such a dictionary. Thank you!

You should understand that dictionaries cannot contain duplicate keys, so this is not possible. What else do you have in mind? — cs95
– cs95, Commented Oct 4, 2017 at 3:33

cs95 · Accepted Answer · 2017-10-04 03:53:31Z

3

melt + set_index + to_dict:

df

     head drowsiness sweat
0  head_P        D_P  sw_f
1  head_S        D-H  sw_h
2  head_F        D_L  sw_l

df.melt().set_index('value').to_dict()['variable']

{'D-H': 'drowsiness',
 'D_L': 'drowsiness',
 'D_P': 'drowsiness',
 'head_F': 'head',
 'head_P': 'head',
 'head_S': 'head',
 'sw_f': 'sweat',
 'sw_h': 'sweat',
 'sw_l': 'sweat'}

If you get this error:

AttributeError: 'DataFrame' object has no attribute 'melt

That means you're using an older version of pandas (<0.20), so instead, use pd.melt:

pd.melt(df).set_index('value').to_dict()['variable']

edited Oct 4, 2017 at 3:53

answered Oct 4, 2017 at 3:40

cs95

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2 Comments

Mary Over a year ago

it returns the following error: AttributeError: 'DataFrame' object has no attribute 'melt'

cs95 Over a year ago

@Mary You must be using an old version of pandas. Change to pd.melt(df).set_index('value').to_dict()['variable']

BENY · Accepted Answer · 2017-10-04 03:53:16Z

3

Add T

df.melt().set_index('value').T.to_dict('records')
Out[277]: 
[{'D-H': 'drowsiness',
  'D_L': 'drowsiness',
  'D_P': 'drowsiness',
  'head_F': 'head',
  'head_P': 'head',
  'head_S': 'head',
  'sw_f': 'sweat',
  'sw_h': 'sweat',
  'sw_l': 'sweat'}]

answered Oct 4, 2017 at 3:53

BENY

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Comments

piRSquared · Accepted Answer · 2017-10-04 04:00:39Z

3

Option 1

dict(zip(df.values.ravel(), df.columns.repeat(len(df))))

{'D-H': 'drowsiness',
 'D_L': 'sweat',
 'D_P': 'head',
 'head_F': 'sweat',
 'head_P': 'head',
 'head_S': 'drowsiness',
 'sw_f': 'head',
 'sw_h': 'drowsiness',
 'sw_l': 'sweat'}

Option 2

dict((v, h) for r, h in zip(df.values, df.columns) for v in r)

{'D-H': 'drowsiness',
 'D_L': 'sweat',
 'D_P': 'head',
 'head_F': 'sweat',
 'head_P': 'head',
 'head_S': 'drowsiness',
 'sw_f': 'head',
 'sw_h': 'drowsiness',
 'sw_l': 'sweat'}

edited Oct 4, 2017 at 4:00

answered Oct 4, 2017 at 3:54

piRSquared

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1 Comment

BENY Over a year ago

dude nice one :)

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